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Nurse effects on measurement error in household biosocial surveys

BACKGROUND: Biosocial survey data are in high demand, yet little is known about the measurement quality of health measures collected by nurses in respondents’ homes. Our objective was to analyze the degree to which nurses influence measurement in anthropometric and physical performance indicators co...

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Autores principales: Cernat, Alexandru, Sakshaug, Joseph W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7047401/
https://www.ncbi.nlm.nih.gov/pubmed/32106825
http://dx.doi.org/10.1186/s12874-020-00922-2
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author Cernat, Alexandru
Sakshaug, Joseph W.
author_facet Cernat, Alexandru
Sakshaug, Joseph W.
author_sort Cernat, Alexandru
collection PubMed
description BACKGROUND: Biosocial survey data are in high demand, yet little is known about the measurement quality of health measures collected by nurses in respondents’ homes. Our objective was to analyze the degree to which nurses influence measurement in anthropometric and physical performance indicators collected from respondents in two nationally-representative UK biosocial surveys. METHODS: The English Longitudinal Survey of Ageing and the UK Household Longitudinal Study – Understanding Society were used to analyze fourteen anthropometric and physical performance measures covering weight, height, pulse, grip strength, and lung capacity. Cross-classified multilevel models were used to estimate “nurse effects” on measurement error. RESULTS: Overall, there is a medium effect of nurses on measurement. Across all measures collected in both studies, nurses explain around 13% of all measurement variation. Variation in specific measures range between approximately 2 and 25%. Grip strength and lung capacity are more heavily influenced by nurses than are height, weight, and pulse. Lastly, nurse characteristics explain only a very small proportion of nurse measurement variation. CONCLUSION: Objective health measures collected by nurses in household biosocial surveys are susceptible to non-trivial amounts of measurement variation. Nurse ID numbers should be regularly included in biosocial data releases to allow researchers to account for this unnecessary source of variation. Further, researchers are advised to conduct sensitivity analyses using control variables that account for nurse variation to confirm whether their substantive findings are influenced by nurse measurement effects.
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spelling pubmed-70474012020-03-03 Nurse effects on measurement error in household biosocial surveys Cernat, Alexandru Sakshaug, Joseph W. BMC Med Res Methodol Research Article BACKGROUND: Biosocial survey data are in high demand, yet little is known about the measurement quality of health measures collected by nurses in respondents’ homes. Our objective was to analyze the degree to which nurses influence measurement in anthropometric and physical performance indicators collected from respondents in two nationally-representative UK biosocial surveys. METHODS: The English Longitudinal Survey of Ageing and the UK Household Longitudinal Study – Understanding Society were used to analyze fourteen anthropometric and physical performance measures covering weight, height, pulse, grip strength, and lung capacity. Cross-classified multilevel models were used to estimate “nurse effects” on measurement error. RESULTS: Overall, there is a medium effect of nurses on measurement. Across all measures collected in both studies, nurses explain around 13% of all measurement variation. Variation in specific measures range between approximately 2 and 25%. Grip strength and lung capacity are more heavily influenced by nurses than are height, weight, and pulse. Lastly, nurse characteristics explain only a very small proportion of nurse measurement variation. CONCLUSION: Objective health measures collected by nurses in household biosocial surveys are susceptible to non-trivial amounts of measurement variation. Nurse ID numbers should be regularly included in biosocial data releases to allow researchers to account for this unnecessary source of variation. Further, researchers are advised to conduct sensitivity analyses using control variables that account for nurse variation to confirm whether their substantive findings are influenced by nurse measurement effects. BioMed Central 2020-02-27 /pmc/articles/PMC7047401/ /pubmed/32106825 http://dx.doi.org/10.1186/s12874-020-00922-2 Text en © The Author(s) 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Cernat, Alexandru
Sakshaug, Joseph W.
Nurse effects on measurement error in household biosocial surveys
title Nurse effects on measurement error in household biosocial surveys
title_full Nurse effects on measurement error in household biosocial surveys
title_fullStr Nurse effects on measurement error in household biosocial surveys
title_full_unstemmed Nurse effects on measurement error in household biosocial surveys
title_short Nurse effects on measurement error in household biosocial surveys
title_sort nurse effects on measurement error in household biosocial surveys
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7047401/
https://www.ncbi.nlm.nih.gov/pubmed/32106825
http://dx.doi.org/10.1186/s12874-020-00922-2
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